Inaugural Lecture by Tjalling Bosse | “The rise of AI in pathology has made a big impression on me”
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What is the core message of your inaugural lecture, and why did you choose this topic?
“A diagnosis is the name of a disease. In traditional pathology, it is based on the visual features observed under the microscope. This diagnosis is not always meaningful when it comes to the questions a patient has. For example, regarding chances of recovery, heredity, or the question of which treatment is best. Pathology can make an important contribution here by incorporating the disease mechanism into the diagnosis. Furthermore, through the use of digitization and AI, we can perform even better measurements on the microscopic image, allowing us to extract all the information it contains. The motivation behind this core message of my inaugural lecture is personal. I, too, have faced serious diagnoses in my personal life and have therefore experienced how frustrating it is when a disease is merely a meaningless name.”
What are some of the key research areas you and your team are currently working on?
“Gynecologic oncology is a rapidly evolving field, with many research areas and numerous collaborations. At LUMC, there is a strong focus on uterine cancer research, as we are also leading several major international studies, such as the PORTEC and RAINBO trials. From the pathology perspective, we’re studying which molecular characteristics might help make the diagnosis more informative. We also started using AI a few years ago to analyze microscopic images.”
What role do education and care play in your vision for this field?
“Education ensures that new doctors learn to think critically and continue to develop. I think it’s important to stimulate curiosity and teach students to ask good questions. At the same time, we prepare them for a profession that is rapidly changing due to digitization and artificial intelligence (AI). Collaboration between healthcare, education, and research is necessary to continue making progress.”
What is something from the past few years that has really stuck with you?
“What has stuck with me the most is how quickly molecular classification of uterine cancer has been adopted in clinical practice. What began as basic scientific research now has a direct impact on treatment decisions worldwide. In addition, the rise of AI in pathology has made a big impression on me. The moment we saw that an AI model could predict outcomes better than existing prognostic models was both confronting and inspiring. It shows that there are still many opportunities to further improve diagnostics.”
How do patients and society benefit from your work?
“Patients benefit from more meaningful precision diagnoses, ensuring treatments are more appropriate. This leads to fewer unnecessary treatments and fewer side effects. Sometimes it actually means a patient receives more intensive treatment, if necessary. For society, this can help keep healthcare affordable by preventing unnecessary tests and treatments. We’re also making advanced diagnostics more accessible, for example in countries or hospitals where expensive tests aren’t available. Ultimately, it’s about the right care, for the right patient, at the right time.”
If we’re allowed to dream, where do you hope the field will be in 10 to 15 years?
“I hope that pathology will have evolved into a field where different types of data—such as tissue characteristics, molecular information, and AI—are effectively integrated. Diagnoses will then not only describe what can be seen, but will also provide immediate information about the best treatment and the expected outcome. Digital and AI-supported diagnostics will be available worldwide, ensuring that patients outside major hospitals also receive quality care. At the same time, the pathologist will continue to play a key role in understanding and utilizing this information. The collaboration between humans and technology must lead to truly personalized care.”
